A neural network prediction of conversion of benzothiophene oxidation catalyzed by nano-Ti-beta catalyst
| Autor: | Uttam Maity, Sonali Sengupta, Jayanta Kumar Basu |
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| Rok vydání: | 2013 |
| Předmět: |
General Chemical Engineering
Organic Chemistry Kinetics Batch reactor Energy Engineering and Power Technology Benzothiophene Catalysis chemistry.chemical_compound Fuel Technology chemistry Chemical engineering Nano Organic chemistry Hydrogen peroxide Beta (finance) High-resolution transmission electron microscopy |
| Zdroj: | Fuel. 113:180-186 |
| ISSN: | 0016-2361 |
| DOI: | 10.1016/j.fuel.2013.05.079 |
| Popis: | The oxidation of benzothiophene (BT) in isooctane with hydrogen peroxide was performed in a batch reactor in a non-severe condition using nano-crystalline Ti-beta catalyst synthesized by dry gel conversion method. The Ti-beta catalyst was characterized by XRD and HRTEM analysis. A three layered feedforward neural network was employed to predict the BT conversion with respect to reaction time, catalyst concentration, hydrogen peroxide to BT mole ratio, temperature and initial BT concentration. The sensitivity analysis of process parameters showed that the BT conversion is highly sensitive to the reaction time, initial BT concentration and temperature. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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